Published October 31, 2017 | Updated January 29, 2019 | 9 minute read
I’ve always had a fraught relationship with numbers and data. Some of my earliest memories are of doing math with my grandmother, a retired Hong Kong math school teacher who was determined that I would follow in the science PhD footsteps of my immigrant parents — or at the very least, not shame the family name by being bad at math. When it turned out that I had no “natural” facility for the subject (or at least, the brilliance that would be expected from a good Chinese girl), I did EPGY online training programs (the alternative to Kumon) and had a math tutor for all of middle and high school. It looked like my path to math proficiency had been successfully remediated — until I sat in the first day of my freshman Calculus AB class, realized I was way in over my head, and swore off all math for the rest of my college career.
This proved to not be completely possible because as a double social science major in psychology and sociology, I had to take Statistics for both. But still, people made sense to me — numbers did not. But my rigorous childhood regimen must have stuck with me more than I realized, because for the next five or so years, every job I had required me to work in data and analysis in some capacity — first as a clinical psychology research assistant and later within the evaluation department of a large social service agency.
But it wasn’t until I started building programs to help other social service agencies across the state turn around their failing businesses that I truly started to see the value that data could bring in transforming organizations. That was the first experience in my journey to becoming a data champion at August today — and along the way, I’ve learned critical lessons in how data can be a critical force for decision-making, driving inclusion, and understanding the why.
Lesson 1: Data as a powerful decision-making tool
As I started to work with managers of the different agencies, it emerged that the core need was teaching them business fundamentals — skills that they had never learned as social workers who had risen up the ranks because of their clinical skills, not business acumen. As leaders, they needed a entirely new set of skills to run their nonprofit business. Without understanding their core business model, and the implication of different staffing changes, cost expenditures, or revenue shifts, they were flying blind in the midst of massive regulatory change.
The leaders who thrived, and who found success in transforming their organizations, embraced data as a way to make better decisions for their people, and most importantly, their patients — to identify which patients were engaged in traditional treatment vs those who needed alternative interventions, therapist engagement and productivity levels, and support staff effectiveness. They actively used data to inform staffing changes, the creation of new processes, and engaged their staff in using the data to monitor the status of their patients. These changes were made necessary by the industry greater shift towards outcomes-based healthcare and also represented an opportunity for these organizations to truly take a hard look at their impact.
This approach was and still is unpopular for traditionalists within a profession that still mostly relies on the art of intuition than scientific rigor. But I saw firsthand that using data to drive accountability for patient outcomes resulted in successful organizations and in turn, healthier patients. And I learned a larger lesson that by actively using data to accelerate and inform decision-making, the data collection and analysis work that often feels tedious and not value-added is truly worth it when fully embedded into work processes and actively leveraged by leaders invested in driving change.
Lesson 2: Data as the foundation for forming a strategic perspective and articulate the why
At Wharton, I continued my data appreciation journey. It was hard not to at a traditionally finance-oriented school, where numbers and data are a fundamental part of almost every class (including those you might assume would be more qualitatively oriented: innovation, creativity, brand management, etc).
But all the emphasis on numbers, algorithms, and sophisticated statistical analyses was also linked to the tendency of both my professors and classmates to use the lack of available quantitative data as an excuse for inaction and as a reason for shutting down alternative opinions that weren’t based on the “right” analysis. These are also dynamics I see play out in my client work with big corporations as well. But I believe that comprises a misuse of data, and also an overemphasis on a specific type of data that distracts from the larger potential at hand.
Often, when we hear about data (and these days, increasingly “big data”) — we think of the complex machinations of numbers identifying correlations and disparate relationships in ways too intimidating to understand. But there is also small data, seemingly insignificant insights or observations that inform the initial hypotheses we then validate with the numbers, and which ultimately, tells us the why of it all.
Small data was what drove the insights I identified in the design research I conducted with women who had experienced miscarriages — which subsequently informed the development of the PEACE Center at Penn Medicine. And it was the combination of using the small data from customer interviews combined with supporting statistical analyses that led the YCAB Cooperative in Indonesia to adopt my Wharton International Volunteer Consultant team’s recommendation to add new loan products to their micro-finance program.
Without small data, the patterns we see in our number crunching and complex statistical models have no meaning or explanation. And, for those who find the numbers overwhelming like I once did, small data is much more accessible. It can be gathered from a conversation, micro-interaction, or observation. Everyone has access to small data and can draw connections, recognize patterns, and articulate insights. They can use small data to truly inform a strategic perspective on where to go and what to do next.
Ultimately, the trick here is that moderation is key. My time at Wharton taught me that the truly effective use of data comprises the marriage between the quant and qual coming together to provide a much more nuanced, insightful view of what to do, what strategy to pursue and ultimately define the why behind what action we pursue.
Lesson 3: Data as a lever to drive greater inclusivity
And so it is that at August, an organizational transformation company that focuses almost entirely on the “soft” side of change, engaging leaders, teams and organizations in shifting their mindsets and behaviors to be more collaborative, transparent and autonomous, I’ve found myself to be the ultimate data champion. This entails pushing us as a company to not just always rely on our expertise and intuition but also look to objective measures to help drive our decisions. You can read more about how that plays out in practice in my previous post, but all to say that I’ve become increasingly convinced that within a self-managed, self-organizing system, the use of data, mostly small, is critical to create and drive a more inclusive organization.
In the absence of data, in moments of uncertainty, there can be a tendency to continually default to the most senior or experienced person in the room — the very dynamic that self-organizing systems are supposed to fight against. Think of how in traditional consultancies, the entry-level analyst gets their power and influence— they have no personal knowledge to bring to the table, but what they do have is time (relatively speaking). Time to run analyses, to do desk research, to become a store of all knowledge related to the problem to be solved. The more senior consultants might have a better intuition of what to do with all that knowledge based on their past experience, but they, and in some cases, the client, listen to what the analyst has to say as an expert in the topic at hand.
In our work, we deliberately use practices and skills like Rounds, structured Feedback, and hands-on Facilitation to give a voice to people who have traditionally been marginalized in both our client work and within our organization. However, its still true that it can be difficult for the less experienced to quickly gain a voice, both with our clients and within our organization. And, there are other factors besides expertise that privilege certain voices over others —the conscious and unconscious biases we hold, due to age, gender, race, sexual orientation…the list goes on.
And that’s where data can play a more powerful role. By starting to embed data, both big and small, into how we target our interventions, how we focus our sales, how we develop our people, we can continue to create a more inclusive environment where everyone’s voice and perspective can have power, and enable our self-organizing system to continue functioning even when the way forward is uncertain.
This requires work — both in the mindset shift required to push ourselves to lean towards data before we lean towards opinion, and in putting the systems and processes in place to enable the meaningful use of data. And this is not to say that data is the solution to creating a truly diverse and inclusive self-organizing system. The conscious and unconscious exercise of power and privilege (which I’ve written more on here) is a critical, significant barrier that gets in our way.
And, this is also not to say that expertise is not critically important in helping drive the way. The knowledge of our more seasoned team members has been hard-won over time, and reflects years of lessons learned that a few numbers or small data nuggets can never replace. But what the strategic use of data can do is create more of a voice for those who have yet to gain the experience and also help accelerate their progress along the way.
Data, Data, Data. What’s next?
So how does this actually work in practice? We’ve started embedding the use of data into our client work, marketing strategies, and business development, and articulated this strategy at our leadership team, all in the spirit of becoming a more #datadriven organization. (Look out for more on this in coming posts).
Ultimately, I believe that data has enormous power for good. We see this today in the rise of big data, where algorithms, not people, are increasingly making decisions that save people’s lives in fields across healthcare, transportation, manufacturing and so on. But even in moments between people, data can still be enormously impactful in divining the why, making more effective decisions, and creating more space for all voices in the room. In the world we strive for, in the complex world we live in, where organizations need to transform, articulate their purpose, and create environments where people at all levels can thrive, data can play a powerful role in driving lasting and systemic change.Thanks to Max Sather.